Skip to main content
SpringerLink
Log in

A fast partial distortion-based motion estimation algorithm in Walsh–Hadamard domain

  • Original Paper
  • Published:
Signal, Image and Video Processing Aims and scope Submit manuscript

Abstract

This paper proposes a fast partial distortion-based block matching motion estimation algorithm and its enhanced version in Walsh–Hadamard. The proposed algorithms divide the current block into sub-blocks and provide a sequence of fine-partial distortions to reject the impossible candidates using as less calculation as possible. In contrast to the previous algorithms in the Walsh–Hadamard domain, such as transform-domain successive elimination algorithm (TSEA) and multilevel transform-domain partial distortion search (MT-PDS) algorithm, these algorithms apply Walsh–Hadamard Transform (WHT) to only those sub-blocks that demand instead of entire block or all sub-blocks. In addition, unlike in the TSEA and MT-PDS algorithms, the number of additional transform coefficients required to calculate partial distortion at any level is constant and small. The simulation results show that the proposed algorithm reduces the computational cost of TSEA and MT-PDS algorithms while maintaining the motion prediction quality. Compared with the full search, 94.95% of the computational complexity is reduced by the proposed algorithm without any reduction in the motion prediction quality. Similarly, the proposed algorithm reduces the computational complexity of the TSEA and MT-PDS algorithms by 28.88% and 42.31%, respectively, without any loss in the motion prediction quality. The enhanced version reduces the computations of proposed algorithm significantly with a slight reduction in motion prediction quality.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

Data availability

Data sharing is not applicable.

References

  1. ITU-T Rec. H.264 and ISO/IEC 14496–10 (MPEG4-AVC), Advanced Video Coding for Generic Audiovisual Services, v1, May, 2003; v2, Jan. 2004; v3 (with FRExt), Sept. 2004; v4, July 2005

  2. J.−B. Lee, H. Kalva (2008) The VC-1 and H.264 Video Compression Standards for Broadband Video Services. Springer, New York

  3. ITU-T Rec. H.263, Video Coding for Low Bit Rate Communication, v1, Nov. 1995; v2, Jan. 1998; v3, Nov. 2000

  4. Li, R., Zeng, B., Liou, M.L.: A new three-step search algorithm for block motion estimation. IEEE Trans. Circuits Syst. Video Technol. 4(4), 438–442 (1994)

    Article  Google Scholar 

  5. Zhu, S., Ma, K.K.: A new diamond search algorithm for fast block-matching motion estimation. IEEE Trans. Image Process. 9(2), 287–290 (2000)

    Article  Google Scholar 

  6. Po, L.M., Ng, K.H., Cheung, K.W., Wong, K.M., Uddin, Y.M., Ting, C.W.: Novel directional gradient descent searches for fast block motion estimation. IEEE Trans. Circuits Syst. Video Technol. 19(8), 1189–1195 (2009)

    Article  Google Scholar 

  7. Zhu, C., Lin, X., Chau, L.P.: Hexagon-based search pattern for fast block motion estimation. IEEE Trans. Circuits Syst. Video Technol. 12(5), 349–355 (2002)

    Article  Google Scholar 

  8. Zou, B.-J., Shi, C., Xu, C.-H., Chen, S.: Enhanced hexagonal-based search using direction-oriented inner search for motion estimation. IEEE Trans. Circuits Syst. Video Technol. 20(1), 156–160 (2010)

    Article  Google Scholar 

  9. Cheungand, C.-H., Po, L.-M.: Novel cross-diamond-hexagonal search algorithms for fast block motion estimation. IEEE Trans. Multimed. 7(1), 16–22 (2005)

    Article  Google Scholar 

  10. Kuo, C.M., Kuan, Y.H., Hsieh, C.H., Lee, Y.H.: A novel prediction-based directional asymmetric search algorithm for fast block-matching motion estimation. IEEE Trans. Circuits Syst. Video Technol. 19(6), 893–899 (2009)

    Article  Google Scholar 

  11. Ko, Y.H., Kang, H.S., Lee, S.W.: Adaptive search range motion estimation using neighboring motion vector differences. IEEE Trans. Consum. Electron. 57(2), 726–730 (2011)

    Article  Google Scholar 

  12. Huang, S.Y., Cho, C.Y., Wang, J.S.: Adaptive fast block-matching algorithm by switching search patterns for sequences with wide-range motion content. IEEE Trans. Circuits Syst. Video Technol. 15(11), 1373–1384 (2005)

    Article  Google Scholar 

  13. Ng, K.H., Po, L.M. and Wong, K.M.: Search patterns switching for motion estimation using rate of error descent. In: IEEE International Conference on Multimedia and Expo, pp. 1583–1586 (2007)

  14. Ng, K.H., Po, L.M., Wong, K.M., Ting, C.W., Cheung, K.W.: A search patterns switching algorithm for block motion estimation. IEEE Trans. Circuits Syst. Video Technol. 19(5), 753–759 (2009)

    Article  Google Scholar 

  15. Dikbas, S., Arici, T., Altunbasak, Y.: Fast motion estimation with interpolation-free sub-sample accuracy. IEEE Trans. Circuits Syst. Video Technol. 20(7), 1047–1051 (2010)

    Article  Google Scholar 

  16. Lin, Y., Wang, Y.C.: Improved parabolic prediction-based fractional search for H.264/AVC video coding. Image Process. IET 3(5), 261–271 (2009)

    Article  Google Scholar 

  17. Li, W., Salari, E.: Successive elimination algorithm for motion estimation. IEEE Trans. Image Process. 4, 105–107 (1995)

    Article  Google Scholar 

  18. Gao, X.Q., Duanmu, C.J., Zou, C.R.: A multilevel successive elimination algorithm for block matching motion estimation. IEEE Trans. Image Process. 9, 501–504 (2000)

    Article  Google Scholar 

  19. Zhu, C., Qi, W.S., Ser, W.: Predictive fine granularity successive elimination for fast optimal block matching motion estimation. IEEE Trans. Image Process. 14(2), 213–221 (2005)

    Article  Google Scholar 

  20. Liu, S.W., Wei, S.D., Lai, S.H.: Fast optimal motion estimation based on gradient-based adaptive multilevel successive elimination. IEEE Trans. Circuits Syst. Video Technol. 18(2), 156–160 (2008)

    Google Scholar 

  21. Jung, J.H., Lee, H.S., Lee, J.H., Park, D.J.: A novel template matching scheme for fast full-search boosted by an integral image. IEEE Signal Process. Lett. 17(1), 107–110 (2010)

    Article  Google Scholar 

  22. Kim, J.N., Kang, D.K., Byun, S.C., Lee, I.L., Ahn, B.H.: A fast full-search motion estimation algorithm using sequential rejection of candidates from hierarchical decision structure. IEEE Trans. Broadcast. 48(1), 43–46 (2002)

    Article  Google Scholar 

  23. ITU-T Recommendation H.263 Software Implementation, Digital Video Coding Group, Telenor R&D (1995)

  24. Eckart, S., Fogg, C.: ISO/IEC MPEG-2 software video codec. Proc. SPIE 2419, 100–118 (1995)

    Article  Google Scholar 

  25. Cheung, C.K., Po, L.M.: Normalized partial distortion search algorithm for block motion estimation. IEEE Trans. Circuits Syst. Video Technol. 10(3), 417–422 (2000)

    Article  Google Scholar 

  26. Cheung, C.K., Po, L.M.: Adjustable partial distortion search algorithm for fast block motion estimation. IEEE Trans. Circuits Syst. Video Technol. 13(1), 100–110 (2003)

    Article  Google Scholar 

  27. Hui, K.C., Siu, W.C., Chan, Y.L.: New adaptive partial distortion search using clustered pixel matching error characteristic. IEEE Trans. Image Process. 14(5), 597–607 (2005)

    Article  Google Scholar 

  28. Cheung, C.-H., Po, L.-M.: A fast block motion estimation using progressive partial distortion search. In: Proceedings of International Symposium on Intelligent Multimedia, Video and Speech Processing, pp. 506–509 (2001)

  29. Lengwehasatit, K., Ortega, A.: Probabilistic partial-distance fast matching algorithms for motion estimation. IEEE Trans. Circuits Syst. Video Technol. 11(2), 139–152 (2001)

    Article  Google Scholar 

  30. Quaglia, D., Montrucchio, B.: Sobol partial distortion algorithm for fast full search in block motion estimation. In: Proceedings of 6th Eurographics Workshop Multimedia, pp. 77–84 (2001)

  31. Montrucchio, B., Quaglia, D.: New sorting-based lossless motion estimation algorithms and a partial distortion elimination performance analysis. IEEE Trans. Circuits Syst. Video Technol. 15(2), 210–220 (2005)

    Article  Google Scholar 

  32. Chun-Su, P.: Multilevel motion estimation based on distortion measure in transform domain. Electron. Lett. 49(14), 880–882 (2013)

    Article  Google Scholar 

  33. Dong, L., Pan, Z.: Fast motion estimation algorithm using multilevel distortion search in Walsh-Hadamard domain. IET Image Process. 11(1), 22–30 (2017)

    Article  Google Scholar 

  34. Subathra, M.S.P., Mohammed, M.A., Maashi, M.S., Garcia-Zapirain, B., Sairamya, N.J., George, S.T.: Detection of focal and non-focal electroencephalogram signals using fast Walsh-Hadamard transform and artificial neural network. Sensors 20(17), 4952 (2020)

    Article  Google Scholar 

  35. Pan, H., Badawi, D., Cetin, A.E.: Fast Walsh–Hadamard transform and smooth-thresholding based binary layers in deep neural networks. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, pp. 4650–4659 (2021)

Download references

Author information

Authors and Affiliations

  1. Department of Electronics and Communication Engineering, MRCET, Hyderabad, Telangana, India

    Kiran Kumar Vemula

  2. Department of Electrical, Electronics and Communication Engineering, GITAM Visakhapatnam, Visakhapatnam, AP, India

    S. Neeraja

Authors
  1. Kiran Kumar Vemula
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. S. Neeraja
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kiran Kumar Vemula.

Ethics declarations

Conflict of interest

The authors declare that they have no conflicts of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Vemula, K.K., Neeraja, S. A fast partial distortion-based motion estimation algorithm in Walsh–Hadamard domain. SIViP 17, 651–659 (2023). https://doi.org/10.1007/s11760-022-02272-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11760-022-02272-6

Keywords

Search

Navigation